Programmable image associative memory using an optical disk and a photorefractive crystal

The optical disk is a computer-addressable binary storage medium with very high capacity. More than 10^10 bits of information can be recorded on a 12-cm-diameter optical disk. The natural two-dimensional format of the data recorded on an optical disk makes this medium particularly attractive for the storage of images and holograms, while parallel access provides a convenient mechanism through which such data may be retrieved. In this paper we discuss a closed-loop optical associative memory based on the optical disk. This system incorporates image correlation, using photorefractive media to compute the best association in a shift-invariant fashion. When presented with a partial or noisy version of one of the images stored on the optical disk, the optical system evolves to a stable state in which those stored images that best match the input are temporally locked in the loop

Acceleration effect of coupled oscillator systems

We have developed a curved isochron clock (CIC) by modifying the radial isochron clock to provide a clean example of the acceleration (deceleration) effect. By analyzing a two-body system of coupled CICs, we determined that an unbalanced mutual interaction caused by curved isochron sets is the minimum mechanism needed for generating the acceleration (deceleration) effect in coupled oscillator systems. From this we can see that the Sakaguchi and Kuramoto (SK) model which is a class of non-frustrated mean feild model has an acceleration (deceleration) effect mechanism. To study frustrated coupled oscillator systems, we extended the SK model to two oscillator associative memory models, one with symmetric and one with asymmetric dilution of coupling, which also have the minimum mechanism of the acceleration (deceleration) effect. We theoretically found that the {\it Onsager reaction term} (ORT), which is unique to frustrated systems, plays an important role in the acceleration (de! celeration) effect. These two models are ideal for evaluating the effect of the ORT because, with the exception of the ORT, they have the same order parameter equations. We found that the two models have identical macroscopic properties, except for the acceleration effect caused by the ORT. By comparing the results of the two models, we can extract the effect of the ORT from only the rotation speeds of the oscillators.Comment: 35 pages, 10 figure

Coupled-Oscillator Associative Memory Array Operation for Pattern Recognition

Operation of the array of coupled oscillators underlying the associative memory function is demonstrated for various interconnection schemes (cross-connect, star phase keying and star frequency keying) and various physical implementation of oscillators (van der Pol, phase-locked loop, spin torque). The speed of synchronization of oscillators and the evolution of the degree of matching is studied as a function of device parameters. The dependence of errors in association on the number of the memorized patterns and the distance between the test and the memorized pattern is determined for Palm, Furber and Hopfield association algorithms

A Model of Stimulus-Specific Neural Assemblies in the Insect Antennal Lobe

It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABAA-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABAA and GABAB inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABAB synapses make the neural response unpredictable. Depending on the balance between GABAA and GABAB inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies

The Kuramoto model: A simple paradigm for synchronization phenomena

Synchronization phenomena in large populations of interacting elements are the subject of intense research efforts in physical, biological, chemical, and social systems. A successful approach to the problem of synchronization consists of modeling each member of the population as a phase oscillator. In this review, synchronization is analyzed in one of the most representative models of coupled phase oscillators, the Kuramoto model. A rigorous mathematical treatment, specific numerical methods, and many variations and extensions of the original model that have appeared in the last few years are presented. Relevant applications of the model in different contexts are also included

Maiter: An Asynchronous Graph Processing Framework for Delta-based Accumulative Iterative Computation

Myriad of graph-based algorithms in machine learning and data mining require parsing relational data iteratively. These algorithms are implemented in a large-scale distributed environment in order to scale to massive data sets. To accelerate these large-scale graph-based iterative computations, we propose delta-based accumulative iterative computation (DAIC). Different from traditional iterative computations, which iteratively update the result based on the result from the previous iteration, DAIC updates the result by accumulating the "changes" between iterations. By DAIC, we can process only the "changes" to avoid the negligible updates. Furthermore, we can perform DAIC asynchronously to bypass the high-cost synchronous barriers in heterogeneous distributed environments. Based on the DAIC model, we design and implement an asynchronous graph processing framework, Maiter. We evaluate Maiter on local cluster as well as on Amazon EC2 Cloud. The results show that Maiter achieves as much as 60x speedup over Hadoop and outperforms other state-of-the-art frameworks.Comment: ScienceCloud 2012, TKDE 201

Integrating Spatial Working Memory and Remote Memory: Interactions between the Medial Prefrontal Cortex and Hippocampus

In recent years, two separate research streams have focused on information sharing between the medial prefrontal cortex (mPFC) and hippocampus (HC). Research into spatial working memory has shown that successful execution of many types of behaviors requires synchronous activity in the theta range between the mPFC and HC, whereas studies of memory consolidation have shown that shifts in area dependency may be temporally modulated. While the nature of information that is being communicated is still unclear, spatial working memory and remote memory recall is reliant on interactions between these two areas. This review will present recent evidence that shows that these two processes are not as separate as they first appeared. We will also present a novel conceptualization of the nature of the medial prefrontal representation and how this might help explain this area’s role in spatial working memory and remote memory recall